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1. The Association Between Risk Factors for Metabolic Syndrome and Meibomian Gland Disease in a Dry Eye Cohort

Author

Mussi N, Haque W, and Robertson DM

Subjects
meibomian gland disease, cholesterol, fasting blood sugar, dry eye, metabolic syndrome, Ophthalmology, RE1-994
Abstract

Natalia Mussi, Waqas Haque, Danielle M Robertson Department of Ophthalmology, The University of Texas Southwestern Medical Center, Dallas, TX, USACorrespondence: Danielle M RobertsonDepartment of Ophthalmology, The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9057, USAEmail Danielle.Robertson@UTSouthwestern.eduPurpose: Risk factors for metabolic syndrome include abdominal obesity, insulin resistance, hypertension, high triglycerides and/or low high-density lipoprotein cholesterol, and hyperglycemia. Risk factors for metabolic syndrome have been associated with dry eye disease; however, their association with meibomian gland disease (MGD), a subtype of dry eye, is unclear. In the present study, we investigated risk factors for metabolic syndrome in a dry eye cohort with and without MGD.Methods: This retrospective case-control study evaluated electronic medical records at a major urban outpatient medical center to identify patients with a known diagnosis of dry eye disease with and without MGD. Males and females were matched for age, smoking status, race, ethnicity, and body mass index (BMI). Patient demographics, anthropometric measurements, medical history, clinical findings, and serologies were analyzed. A diagnosis of MGD was based on clinical signs noted in the medical record.Results: MGD was not associated with BMI, smoking, type 2 diabetes mellitus, hypertension or hyperlipidemia in this dry eye cohort. MGD was associated with male sex and increasing age. While increasing age was weakly correlated with decreased low density lipoprotein cholesterol and non-high density lipoprotein cholesterol, serum lipid levels were not associated with MGD.Conclusion: Importantly, we found that risk factors for metabolic syndrome are not specifically associated with an increase in MGD when compared to non-MGD dry eye subjects. While risk factors for metabolic syndrome are associated with dry eye disease, they likely reflect a chronic systemic state of low-grade inflammation that negatively impacts the function of both lacrimal and meibomian glands.Keywords: meibomian gland disease, cholesterol, fasting blood sugar, dry eye, metabolic syndrome

Published
2021

3. Risk Factors for Diabetic Nephropathy among Newly Detected Type 2 Diabetic Patients Attending a Tertiary Care Hospital of Bangladesh.

Author

RAHIM, M. A., HAQUE, W. M. M. U., AFSANA, F., ZAMAN, S., and IQBAL, S.

Subjects
*DIABETIC nephropathies, *PEOPLE with diabetes, *TYPE 2 diabetes, *URINARY tract infections, *TERTIARY care
Abstract

Background: Patients with type 2 diabetes mellitus may present with different macro- and micro-vascular complications including diabetic nephropathy. This study was designed to evaluate the risk factors for diabetic nephropathy among newly detected type 2 diabetic patients. Methods: This case-control study was done at BIRDEM General Hospital, Dhaka, Bangladesh from January to September 2017. Adult (≥18 years), type 2 diabetic patients, who were detected as diabetic for the first time, within the previous three months and who tested, at least, 2 urine samples for urine albumin to creatinine ratio (UACR), at least 6 weeks apart, were consecutively enrolled for the study. Pregnant ladies, patients with diagnosed kidney disease, patients having features of glomerulonephritis and systemic diseases like vasculitis and systemic lupus erythematosus, history of recent fever, urinary tract infection and menstruation were excluded. Patients having UACR ≥30 mg/g in at least 2 (out of 3, if tested) samples were taken as cases and those with UACR < 30 mg/g were controls. Data were analyzed by statistical package for social sciences (SPSS) version 20. Results: Total patients were 224 with female predominance (150, 67%). Fifty one (22.8%) patients had diabetic nephropathy (microalbuminuria = 47 and overt proteinuria = 4). Multivariate regression analysis revealed that, hypertension [odds ratio (OR) = 3.71; 95% CI 1.23 to 4.31, p = 0.003], smoking (OR = 3.27; 95% CI 2.91 to 4.79, p = 0.003), family history of diabetes (OR = 2.31; 95% CI 1.84 to 3.14, p = 0.005) and diabetic nephropathy (OR = 3.34; 95% CI 2.40 to 4.97, p = 0.001), dyslipidaemia (OR = 2.31; 95% CI 1.98 to 3.91, p = 0.023), increased body mass index (BMI) (OR = 2.11; 95% CI 1.54 to 4.87, p = 0.001 and high glycated haemoglobin (HbA1c) (OR 3.21; 95% CI 1.71 to 5.97, p = 0.034) were significant risk factors for diabetic nephropathy. Conclusion: One in every five type 2 diabetic patients had diabetic nephropathy during diabetes diagnosis and most patients had microalbuminuria. Hypertension, dyslipidaemia, smoking, family history of diabetes and diabetic nephropathy, increased BMI and high HbA1c were significant risk factors for diabetic nephropathy among newly detected type 2 diabetic patients. [ABSTRACT FROM AUTHOR]

Published
2023
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9. 1091P Relapse-free survival with adjuvant dabrafenib/trametinib therapy after relapse on a prior adjuvant checkpoint inhibitor and subsequent surgical resection in patients with BRAF V600-mutated stage III/IV melanoma

Author

Weber, J.S., Haque, W., Markovic, S.N., Salama, A.K.S., Mehmi, I., Sullivan, R.J., Najjar, Y.G., van Akkooi, A.C.J., Menzies, A.M., Long, G.V., Taylor, A.M., Haanen, J.B.A.G., Zijlker, L., Davis, K., Karanth, S., Shah, R., Connolly, L., and Norton, D.

Published
2023
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18. Concept of dirty dozen:the silent killers of human factor errors and mistakes

Author

Ahasan, R. (R), Shahren, A. (AZA), Haque, W. (W), Islam, E. (E), Ahasan, R. (R), Shahren, A. (AZA), Haque, W. (W), and Islam, E. (E)

Abstract

Human Factors (HFs) interactions are important that surely impact the employee behavior at work. HFs interactions that interact with individual worker behavior can complement unintentional consequences at work. Currently, these consequences at work are being seen as the notorious culprits of HFs. Safety policy and systematic procedures of industries and companies seems to be strongly okay, however, dirty dozen concepts are not emphasized in workplace health and safety program. Dirty dozen is the twelve HFs problems that cause human errors or operator mistakes. In many project team applications, these are potential human causal factors that degrade worker skills and abilities. Dirty dozen are the real killers in every workplace environment which are also hidden behind the work process. Hence, this paper explores the basic concepts behind the dirty dozen, the silent killers of HFs errors, which are blamed for degrading worker abilities to perform job-tasks effectively and safely.

Published
2018

26. Polymer Association Structures

Author

MAGDA A. EL-NOKALY, H. Finkelmann, E. Jahns, Tharwat F. Tadros, P. F. Luckham, C. Yanaranop, Stig E. Friberg, Guo Rong, Ch. Ch. Yang, Yun Yang, Françoise Candau, S. Qutubuddin, E. Haque, W. J. Benton, E. J. Fendler, J. S. Guo, M. S. El-Aasser, J. W. Vanderhoff, F. Cuirassier, Ch. H. Baradji, G. Ries

Published
1989

27. Sulfur in Pesticide Action and Metabolism

Author

Joseph D. Rosen, PHILIP S. MAGEE, John E. Casida, ERIC BLOCK, R. A. NEAL, T. R. FUKUTO, M. A. H. FAHMY, D. H. HUTSON, INGOLF SCHUPHAN, YOFFI SEGALL, JOSEPH D. ROSEN, JOHN E. CASIDA, I. SCHUPHAN, D. WESTPHAL, A. HAQUE, W. EBING, CHIA C. KU, INDER P. KAPOOR, FUMIO MATSUMURA, K. YONEYAMA, J. MARSHALL C

Published
1981

30. Clinical nephrology - miscellaneous

Author

Bantis, C., primary, Heering, P., additional, Kouri, N.-M., additional, Siekierka-Harreis, M., additional, Stangou, M., additional, Schwandt, C., additional, Efstratiadis, G., additional, Rump, L.-C., additional, Ivens, K., additional, Haddiya, I., additional, Houssaini Squalli, T., additional, Laouad, I., additional, Ramdani, B., additional, Bayahia, R., additional, Dimas, G. G., additional, Tegos, T. J., additional, Spiroglou, S. G., additional, Pitsalidis, C. G., additional, Sioulis, A. S., additional, Karamouzis, I. M., additional, Savopoulos, C. G., additional, Karamouzis, M. I., additional, Orologas, A. G., additional, Hatzitolios, A. I., additional, Grekas, D. M., additional, Maixnerova, D., additional, Jancova, E., additional, Rychlik, I., additional, Rysava, R., additional, Merta, M., additional, Reiterova, J., additional, Kolsky, A., additional, Honsova, E., additional, Skibova, J., additional, Tesar, V., additional, Kendi Celebi, Z., additional, Calayoglu, R., additional, Keven, K., additional, Kurultak, I., additional, Mescigil, P., additional, Erbay, B., additional, Karatan, O., additional, Duman, N., additional, Erturk, S., additional, Nergizoglu, G., additional, Kutlay, S., additional, Sengul, S., additional, Ates, K., additional, Marino, F., additional, Martorano, C., additional, Bellantoni, M., additional, Tripepi, R., additional, Zoccali, C., additional, Ishizuka, K., additional, Harita, Y., additional, Kajiho, Y., additional, Tsurumi, H., additional, Asano, T., additional, Nishiyama, K., additional, Sugawara, N., additional, Chikamoto, H., additional, Akioka, Y., additional, Yamaguchi, Y., additional, Igarashi, T., additional, Hattori, M., additional, Bantis, C., additional, Heering, P. J., additional, Sahay, M., additional, Monova, D. V., additional, Monov, S. V., additional, Wang, Y.-y., additional, Cheng, H., additional, Wang, G.-q., additional, Dong, H.-r., additional, Chen, Y.-p., additional, Wang, C.-j., additional, Tang, Y.-l., additional, Buti, E., additional, Dervishi, E., additional, Bergesio, F., additional, Ghiandai, G., additional, Mjeshtri, A., additional, Paudice, N., additional, Caldini, A. L., additional, Nozzoli, C., additional, Minetti, E. E., additional, Sun, L., additional, Feng, J., additional, Yao, L., additional, Fan, Q., additional, Ma, J., additional, Wang, L., additional, Kirsanova, T., additional, Merkusheva, L., additional, Ruinihina, N., additional, Kozlovskaya, N., additional, Elenshleger, G., additional, Turgutalp, K., additional, Karabulut, U., additional, Ozcan, T., additional, Helvaci, I., additional, Kiykim, A., additional, Kaul, A., additional, Bhadhuaria, D., additional, sharma, R., additional, Prasad, N., additional, Gupta, A., additional, Clajus, C., additional, Schmidt, J., additional, Haller, H., additional, Kumpers, P., additional, David, S., additional, Sevillano, A. M., additional, Molina, M., additional, Gutierrez, E., additional, Morales, E., additional, Gonzalez, E., additional, Hernandez, E., additional, Praga, M., additional, Conde Olasagasti, J. L., additional, Vozmediano Poyatos, C., additional, Illescas, M. L., additional, Tallon, S., additional, Uson Carrasco, J. J., additional, Roca Munoz, A., additional, Rivera Hernandez, F., additional, Ismail, G., additional, Jurubita, R., additional, Andronesi, A., additional, Bobeica, R., additional, Zilisteanu, D., additional, Rusu, E., additional, Achim, C., additional, Huerta, A., additional, Caro, J., additional, Gutierrez-Solis, E., additional, Pasquariello, A., additional, Pasquariello, G., additional, Innocenti, M., additional, Grassi, G., additional, Egidi, M. F., additional, Ozturk, O., additional, Yildiz, A., additional, Gul, C. B., additional, Dilek, K., additional, Tylicki, L., additional, Jakubowska, A., additional, Weber, E., additional, Lizakowski, S., additional, Swietlik, D., additional, Rutkowski, B., additional, Postorino, A., additional, Costa, S., additional, Cristadoro, S., additional, Magazzu, G., additional, Bellinghieri, G., additional, Savica, V., additional, Buemi, M., additional, Santoro, D., additional, Lu, Y., additional, Shen, P., additional, Li, X., additional, Xu, Y., additional, Pan, X., additional, Wang, W., additional, Chen, X., additional, Zhang, W., additional, Ren, H., additional, Chen, N., additional, Mitic, B. P., additional, Cvetkovic, T., additional, Vlahovic, P., additional, Velickovic Radovanovic, R., additional, Stefanovic, V., additional, Kostic, S., additional, Djordjevic, V., additional, Ao, Q., additional, Ma, Q., additional, Cheng, Q., additional, Wang, X., additional, Liu, S., additional, Zhang, R., additional, Ozturk, S., additional, Ozmen, S., additional, Akin, D., additional, Danis, R., additional, Yilmaz, M., additional, Hajri, S., additional, Barbouche, S., additional, Okpa, H., additional, Oviasu, E., additional, Ojogwu, L., additional, Fotouhi, N., additional, Ghaffari, A., additional, Hamzavi, F., additional, Nasri, H., additional, Ardalan, M., additional, Stott, A., additional, Ullah, A., additional, Anijeet, H., additional, Ahmed, S., additional, Kohli, H. S., additional, Rajachandran, R., additional, Rathi, M., additional, Jha, V., additional, Sakhuja, V., additional, Yenigun, E., additional, Dede, F., additional, Turgut, D., additional, Koc, E., additional, Akoglu, H., additional, Piskinpasa, S., additional, Ozturk, R., additional, Odabas, A., additional, Bajcsi, D., additional, Abraham, G., additional, Kemeny, E., additional, Sonkodi, S., additional, Legrady, P., additional, Letoha, A., additional, Constantinou, K., additional, Ondrik, Z., additional, Ivanyi, B., additional, Lucisano, G., additional, Comi, N., additional, Cianfrone, P., additional, Summaria, C., additional, Piraina, V., additional, Talarico, R., additional, Camastra, C., additional, Fuiano, G., additional, Proletov, I., additional, Saganova, E., additional, Galkina, O., additional, Bogdanova, E., additional, Zubina, I., additional, Sipovskii, V., additional, Smirnov, A., additional, Bailly, E., additional, Pierre, D., additional, Kerdraon, R., additional, Grezard, O., additional, Gnappi, E., additional, Delsante, M., additional, Galetti, M., additional, Maggiore, U., additional, Manenti, L., additional, Hasan, M. J., additional, Muqueet, M. A., additional, Mostafi, M., additional, Chowdhury, I., additional, Haque, W., additional, Khan, T., additional, Kang, Y.-J., additional, Bae, E. J., additional, Cho, H. S., additional, Chang, S.-H., additional, Park, D. J., additional, Xu, G., additional, Lin, H., additional, Hu, Z., additional, Yu, X., additional, Xing, C., additional, Mei, C., additional, Zuo, L., additional, Ni, Z., additional, Ding, X., additional, Li, D., additional, Zhang, Q., additional, Feng, X., additional, and Lin, L., additional

Published
2013
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48. The Patch Helps

Author

Cinciripini, P. M., primary, Cinciripini, L. G., additional, Wallfisch, A., additional, Haque, W., additional, and Van Vunakis, H., additional

Published
1996
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49. High Quality Analytics with Poor Quality Data.

Author

Haque, W. and Edwards, J.

Subjects
*DATA quality, *BUSINESS intelligence, *FORESTS & forestry, *DATA warehousing, *BUSINESS ethics
Abstract

Poor data quality has often been cited as the single most common problem hindering the deployment of Business Intelligence (BI) solutions. This problem is compounded when analytics is performed in non-conventional BI areas such as forestry and silviculture. In this paper, we describe a methodology to perform BI analytics on data that was never collected to be used for this purpose. We show that data of such low and poor quality can be transformed and loaded into the data warehouse which is then used for high quality reporting. [ABSTRACT FROM AUTHOR]

Published
2012
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